repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · 24d ago
guoqingbao/xinfer
Blazing-fast LLM inference in pure Rust. No PyTorch and Python runtime.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
Why these links exist
Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 55%DSpark: Speculative decoding accelerates LLM inference [pdf] →
- PossiblePossibly related (embedding) · 51%Profiling in PyTorch (Part 2): From nn.Linear to a Fused MLP →
- PossiblePossibly related (embedding) · 49%OpenAI and Broadcom announce chip designed for LLM inference at scale →
- PossiblePossibly related (embedding) · 49%Would having a dedicated programming language specifically for LLMs be a viable solution? [D] →
- PossiblePossibly related (embedding) · 49%DeepSeek open-sources inference optimizations with 60–85% faster generation [pdf] →
Covers
newsDSpark: Speculative decoding accelerates LLM inference [pdf]newsProfiling in PyTorch (Part 2): From nn.Linear to a Fused MLPnewsOpenAI and Broadcom announce chip designed for LLM inference at scalenewsWould having a dedicated programming language specifically for LLMs be a viable solution? [D]newsDeepSeek open-sources inference optimizations with 60–85% faster generation [pdf]
Related across the graph
newsProfiling in PyTorch (Part 2): From nn.Linear to a Fused MLPnewsOpenAI and Broadcom announce chip designed for LLM inference at scalenewsWould having a dedicated programming language specifically for LLMs be a viable solution? [D]newsDSpark: Speculative decoding accelerates LLM inference [pdf]newsDeepSeek open-sources inference optimizations with 60–85% faster generation [pdf]